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Externalize BlackboxClassifier dataset (x and predictions)

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abigailt 2022-07-25 15:47:04 +03:00 • committed by abigailgold
parent fb534f7a0f
commit a13415ad67
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10
tests/test_model.py
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@ -12,6 +12,8 @@ from sklearn.ensemble import RandomForestClassifier
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Input
from art.utils import check_and_transform_label_format
from art.utils import to_categorical
@ -158,6 +160,10 @@ def test_blackbox_classifier_no_test():
score = model.score(train)
assert (score == 1.0)
predictions_x, predictions_y = model.get_predictions()
assert np.array_equal(predictions_x, x_train)
assert np.array_equal(predictions_y, check_and_transform_label_format(y_train, nb_classes=3))
def test_blackbox_classifier_no_train():
(_, _), (x_test, y_test) = dataset_utils.get_iris_dataset_np()
@ -171,6 +177,10 @@ def test_blackbox_classifier_no_train():
score = model.score(test)
assert (score == 1.0)
predictions_x, predictions_y = model.get_predictions()
assert np.array_equal(predictions_x, x_test)
assert np.array_equal(predictions_y, check_and_transform_label_format(y_test, nb_classes=3))
def test_blackbox_classifier_no_test_y():
(x_train, y_train), (x_test, _) = dataset_utils.get_iris_dataset_np()